Digging the Dark: Broad-Scale Nesting Patterns of Sea Turtles vis-á-vis Satellite Measures of Artificial Lighting

Being a Florida boy, I go to the beach a lot. About every other year, when relatives or friends visit during the summer, we go on a “turtle walk” at Archie Carr National Wildlife Refuge (ACNWR). The refuge, founded in 1991, is one of 530 national wildlife refuges. ACNWR is 15 miles north of the Pelican Island National Wildlife Refuge, founded in 1903 by Theodore Roosevelt. ACNWR, named after the world’s foremost authority on sea turtles, is home to the highest density of nesting loggerheads (Caretta caretta) in the Western Hemisphere and the highest density of nesting green turtles (Chelonia mydas) in the continental United States (“Archie Carr National Wildlife Refuge”); thus, it is a perfect place to encounter sea turtles.

In June 2014, I made my pilgrimage to ACNWR with some visitors from Rhode Island. Researchers from the University of Central Florida’s Marine Turtle Research Group, wearing headlamps that emitted red light, guided us from the parking lot to the beach. Though Florida nights can be warm, I wore long pants and a jacket to reduce encounters with biting insects. However, there was a sea breeze that kept the flies and mosquitoes at bay. We ambled along above the surf until one guide’s cell phone buzzed. A turtle was nesting 200 yards to the south of us. We turned around and picked up the pace toward a glow of red lights near the dune. About 10 yards away, a guide pointed out the tracks that an approximately 300-pound sea turtle had made when she crawled out of the ocean. We followed the tracks and gathered around the large, still reptile. Red lights were positioned above the nest cavity that she had dug a few minutes before (Figure 1). We watched the ping pong-ball-sized eggs plop one by one on top of the growing pile. 

Figure 1

Figure 1: Researchers measuring the reproductive and morphological parameters from a nesting loggerhead at the Archie Carr National Wildlife Refuge. Red light wavelengths do not interfere with the turtle’s behavior (Witherington). 


Why the red lights? One guide explained that sea turtles are not sensitive to long (red) wavelengths, but they are to shorter (orange-yellow-green-blue) wavelengths. Not only are nesting females deterred by shorter-wavelength light, but when the eggs hatch roughly 60 days later, the hatchlings are often attracted to artificial light and wander away from the ocean toward State Road A1A. In Florida each year, it is estimated that thousands of hatchlings die because they are disoriented by artificial light. The guide also explained that lighting ordinances are in place to reduce artificial light on the beaches during the nesting season (May–August). However, during our walk there were some sections where streetlights and porch lights were visible, and when you looked to the north, there was a large yellow-green sky glow off in the distance from the more populated Cocoa Beach (Figure 2). And Cocoa Beach is tiny compared to Miami, 200 miles to the south. I wondered if Floridians were doing a good job protecting these endangered species, and how the turtles have responded to the new development along the coast that I notice every time I make a trip to the beach.

fig2

Figure 2: Sky glow looking northward from the Archie Carr National Wildlife Refuge in Brevard County, Florida, in June 2014. 

 


 

 

Introduction

As humans appropriate the terrestrial surface of the earth, areas of total darkness are becoming increasingly rare (Bogard). Light pollution (excessive, misdirected, or obtrusive artificial light) is a serious threat to wildlife (Longcore and Rich; Hölker et al.). Artificial light disrupts amphibian, bird, fish, mammal, reptile and invertebrate behaviors and alters movement patterns, which may deplete energy and lead to injury or death. All surface-dwelling organisms (including humans) are genetically adapted to regular day-night and seasonal cycles that have been interrupted by artificial lights (Rich and Longcore). Light pollution is a form of habitat degradation, which is the primary cause of biodiversity loss, which is leading to a sixth major extinction event.

The two sea turtle families (Cheloniidae and Dermochelyidae) have been around since the time of the dinosaurs approximately 100 million years ago. The seven species of sea turtles are globally distributed in temperate and tropical oceans. Though all imperiled, they help to balance marine ecosystems and are sentinels of ocean health. Through their foraging habits, both carnivorous and herbivorous, and nutrient deposition (egg laying), sea turtles have major impacts on ocean food webs and coastal biogeochemical processes (Wilson et al.). Reductions in sea turtle populations have led to massive jellyfish blooms and declining productivity in fisheries.

Human threats to sea turtles are direct, through harvesting for consumption and incidental by-catch, and indirect, through marine pollution (both chemical and from debris) and coastal habitat degradation (through development and beach armoring). Artificial lighting along coasts reduces nocturnal beach nesting habitat. Experimentally, at local scales (10–100 meters), artificial light has been shown to deter gravid females and disorient hatchlings (Witherington; Witheringon and Martin; Salmon). I set out to determine if the deterrent effect of artificial lighting is manifest on broader-scale (1–100 kilometer) nesting patterns.

 

Objectives and Hypotheses

Using satellites to measure habitat quality is an efficient method of monitoring extensive areas systematically. As both satellite and sea turtle nesting records span two decades, I wanted to use archived datasets to evaluate trends and relationships. This study’s primary objectives are to identify trends in light pollution levels from 1992–2012 on nesting beaches and to assess the effects of artificial lighting on the nesting patterns of the three predominate Florida species.

Hypothesis 1: As local ordinances have been enacted across the state, it is expected that there will be declining levels of satellite-detected artificial light over a 21-year period for the sea turtle nesting beaches that are systematically monitored.

Hypothesis 2:If satellite-detected artificial light negatively affects sea turtle nesting behaviors, there will be lower nest densities in those areas where levels of artificial light are high compared to areas where levels are low.

Hypothesis 3: If species’ behavioral responses to artificial light are similar, there will be no differences in relative nesting patterns among the three primary Florida species in relation to light levels.

 

Materials and Methods

Focal Species and Nesting Data

Florida, by far, is the most important state for sea turtle nesting. Five species regularly nest in Florida, in declining order by nest numbers: loggerhead (Caretta caretta), green turtle (Chelonia mydas), leatherback (Dermochelys coriacea), Kemp’s ridley (Lepidochelys kempi), and hawksbill (Eretmochelys imbricata).

The Florida loggerhead rookery makes up 90% of all U.S. loggerhead nesting; it is the largest in Western Hemisphere and second in the world. Loggerheads are categorized as endangered by International Union for the Conservation of Nature (IUCN 1996); Florida populations are listed as threatened by the U.S. Fish and Wildlife Service (USFWS). The population has been fluctuating over the last 30 years. Females nest from April to September, laying 4 to 7 nests (with approximately 115 eggs per nest) and usually return to the same beach every 2 or more years. Based on experiments, loggerheads are thought to be slightly less sensitive to short-wavelength light than green turtles (Fritsches and Warrant).

The Florida green turtle aggregation is the second largest in Western Hemisphere. Green turtles are categorized as endangered by both the International Union for the Conservation of Nature and the U.S. Fish and Wildlife Service, although the Florida population has been exponentially increasing. They nest at 2- to 4-year intervals from June to September, and lay about 3 to 5 nests (with approximately 135 eggs per nest) each season. Green turtles have the lowest overall optical sensitivity to light of the three species (Fritsches and Warrant).

Leatherbacks are the largest and most pelagic sea turtle. Florida is the only continental state where they regularly nest. They are listed as vulnerable by IUCN (2013) and endangered by the U.S. Fish and Wildlife Service. The Florida population has been steadily increasing. Leatherbacks nest from March to July, 5 to 7 times per season (with approximately 80 eggs per nest), and return every 2 to 3 years. They have a high sensitivity to wavelengths around 400 nanometers, but are less sensitive to wavelengths greater than 520 nanometers than loggerhead and green turtles (Fritsches and Warrant).

To conserve these species as mandated by the 1973 Endangered Species Act, the U.S. Fish and Wildlife Service works with the Florida Fish and Wildlife Conservation Commission (FWC) to monitor nesting patterns across the state. In 1989, the commission established the Index Nesting Beach Survey (INBS). The survey follows standard protocols in which trained surveyors and volunteers traverse specific beaches every morning during nesting season (15 May to 31 August) and record nesting by species based on track and digging characteristics (Figure 3). The commission divides the Florida coast into eight nesting regions (Northeast, Central Northeast, Central East, Central Southeast, Southeast, South, Southwest, and Northwest). A total of 28 beaches comprising 368 segments of approximately one square kilometer from six regions have been monitored consistently using INBS standards since the program’s inception (Figure 4). Five more beaches (126 segments) in the Gulf Coast have been added since 1992.

 

fig3

Figure 3: ACNWR beach section showing tracks of nesting sea turtle crawls. The brown arrows are loggerheads, green arrows are green turtles. (Adapted from an unpublished image by the UCF Geospatial Analysis and Modeling of Ecological Systems (GAMES) Lab.)


 

 

fig4

Figure 4: Satellite-recorded nightlights averaged per pixel from 1992 to 2012. Yellow lines are adjacent to surveyed beaches in the six regions that have been monitored consistently since 1992 (the South, which includes the Keys and the Everglades, and the northeast Panhandle regions did not have consistent monitoring during this period). 


I acquired the INBS data (ArcGIS shapefiles and Excel spreadsheets) from the Fish and Wildlife Research Institute (a division of the FWC) for 1992–2012 to coincide with the satellite data. There were 7,728 nesting tallies per species (368 beach segments x 21 years). I calculated the nest density for the state, each region, and each surveyed beach segment for each species and each year (Figure 5) in Excel using segment lengths from the ArcGIS shape files.

 

fig5

Figure 5: Regional dynamics of (A) loggerhead, (B) green turtle, and (C) leatherback nest density. Black markers are the overall average. Extensions represent ±1 standard error.


To better visualize the data, I measured distances along the coastline from the midpoint of each beach segment in ArcGIS and spatially transformed the nesting and light data from latitude-longitude coordinates into one-dimensional, 953.2-kilometer-long transects from Fort Clinch (northeast, 0 kilometers) to Sanibel Island (southwest, 953.2 kilometers), going clockwise around the state (Figure 6).

 

fig6

Figure 6: Average nest densities of (A) loggerhead, (B) green turtle, and (C) leatherback for each surveyed beach over 1992–2012. Dots above the histograms represent standard error. Percentages are the average number of nests by region.


 

Satellite-Derived Artificial Light Data

The Defense Meteorological Satellite Program (DMSP) monitors weather for the Air Force. Visible and infrared sensors collect 3,000-kilometer swaths of data, covering the Earth twice daily. The visible signal is intensified at night to detect moonlit clouds. This enables light detection at the planet surface. Nighttime, cloud-free data (without solar glare, moonlight, and auroral effects) are mapped into a latitude-longitude grid with an equatorial pixel size of  approximately one kilometer. The “Average Lights x Percent” product is the average visible digital number of nightlight detections multiplied by the percent frequency of cloud-free detections (Global DMSP-OLS). I downloaded the satellite imagery data from 1992–2012 from the NOAA National Geophysical Data Center. I rescaled the annual 6-bit data from 0 to 100, with 0 representing total darkness and 100 representing light saturation over the entire year.

In ArcGIS, I clipped the 21 global images (DSMP) to a buffered region around Florida and overlaid the INBS shapefiles with the 21 satellite raster images. Figure 4 shows the average light value for each pixel from 1992–2012. Urban areas—e.g., Jacksonville, Orlando, Miami, and Tampa-St. Petersburg—are red blobs representing maximum light values. I then used the insectlinerst command in the Geospatial Modeling Environment (Beyer) software package to calculate the yearly artificial light value for each beach segment, weighted by the portion of the segment in the raster. As with the nesting data, I calculated the change in light over the 21-year period by region and examined the light by the surveyed beach segment.

To determine the trends for each pixel across the state and for each beach segment, I used the raster calculator in ArcGIS and the slope command in Excel. Artificial light (lgt) trends over the 21-year period for each beach segment and each satellite pixel were determined using the slope (b) formula of a regression line:

zachary_formula

Lastly, to relate the average nesting densities for each species to the average artificial light value, I used the linear regression from the Excel Data Analysis Package, where the average nest density for each beach segment was the dependent variable and the average satellite-derived artificial light value was the independent variable. However, because both data sets were not normally distributed, they were first log-transformed.

Results

The Southeast region, with Miami and Ft. Lauderdale, by far had the highest light levels on its INBS beaches (Figure 7A). The Central Northeast region had the lowest. There were minor year-to-year fluctuations at the regional scale and seemingly little variance, as shown by the small standard errors at the surveyed beach scale (Figure 7B). Across the state, artificial light trends (Figure 8) showed new urbanization (red) around the cities and scattered small darkening areas (blue).

fig7

Figure 7: (A) Regional dynamics of artificial light averages. Black markers are the overall annual averages. F-number refers to different military satellites. (B) Artificial light averages (1992–2012) for each surveyed beach segment. Extensions and dots are standard errors. 


Along the nesting beaches, there were both declines and improvements in dark habitats (Figure 9). Beaches in the Central Northeast and Southwest regions showed a general decline in artificial light levels from 1992–2012. Trends for other regions are more mixed. However, Southeast beaches with nearly maximum light levels during these two decades (Figure 7A) showed little change. Miami Beach showed consistently high light levels, while Canaveral National Seashore showed consistently low levels.

 

fig8

Figure 8: Per-pixel trends of satellite-recorded nightlights over Florida from 1992–2012. Red corresponds to increasing light, blue to declining. Green indicates little change. Brown lines off the coast are adjacent to stretches of the monitored beaches. Two contrasting beach areas (expanded in Figure 10) are designated by purple and orange rectangular boxes.


 

fig9

Figure 9: Artificial light trends along the Florida coast with specific INBS examples. Red indicates a positive slope. Blue indicates a negative slope. 


 

fig10

Figure 10: Areas (small rectangles in Figure 8) showing (A) declines and (B) increases in satellite values on monitored beaches from 1992 (top) to 2012 (bottom). Colored line segments correspond to monitored beach segments. The arrows point to the specific beaches, i.e., Zone 910 (left) and Zone 1408 (right), whose light dynamics over a 21-year period are shown in Figure 9. 


Site-specific light patterns (Figure 10) revealed areas where light management plans were working and where they were not. Average nesting relationships to light were species-dependent  (Figure 11). Loggerhead nest density showed no relationship; green turtles showed some aversion; and leatherbacks showed a significant attraction, though the linear model fits were poor.

fig11

Figure 11: Relationships between average satellite-derived artificial light for the average nest densities of (A) loggerheads, (B) green turtles, and (C) leatherbacks for the 368 monitored beaches.


Discussion and Conclusions

Artificial light is a symptom of coastal development that can have other negative impacts on sea turtle nesting. Florida, with its long coastline, is difficult to monitor on the ground. The 21-year satellite record showed some coastal areas where artificial light declined and some areas where it increased, which suggests that this approach could be used for statewide management or for other extensive (or remote) areas elsewhere. Even with regulations in place, there was no overall declining trend in light levels (H1) along these important nesting beaches. One explanation is that the approximately one-kilometer pixels may not accurately represent the level of light that actually appears on the beach, as dunes, the slope of the beach, or buildings may prevent light from reaching the turtles. Or the detected light could include turtle-friendly wavelengths that the  satellite sensor cannot discriminate. Surprisingly, the only significant relationship between light level and nest density was a positive one for leatherbacks (H2). They are considered to be the least sensitive to light. Loggerhead turtles had a neutral relationship to light levels, and green turtles a slightly negative one, which suggests species differences (H3). A follow-up study should evaluate the response of hatchlings on the differentially lighted beaches detected by satellites, to see if they are affected. However, the simple linear regression approach I used is problematic. Averaging the data over the years reduced my sample size. Also, I need to consider neighborhood effects (spatial autocorrelation) that probably exist for both the dependent and independent variables. This violates the assumption of sample independence, which can be rectified with spatial autoregressive modeling (Kissling and Gudrun). 

Regardless, this scotobiological study of satellite-derived artificial light on sea turtle nesting was the first of its kind in the Western Hemisphere. It was more extensive and covered more significant nesting beaches than a study from Israel (Mazor et al.) and included site-specific, long-term sea turtle nesting data, unlike two Australian studies (Kamrowski et al. 2012; 2014). Though most nest monitoring programs are not as well established as Florida’s, the satellite coverage would permit a global analysis (Figure 12) of artificial light impacts on other sea turtle species and other light-sensitive taxa.

 

fig12

Figure 12: Satellite night light image from 2012, showing the nesting locations of six sea turtle species (Halpin). Circle sizes reflect the quartiles of nest numbers per species.   


Acknowledgments
I would like to thank the University of Central Florida’s Geospatial Analysis and Modeling of Ecological Systems (GAMES) Lab, which provided me with access to image processing and GIS software. Also, I would like to thank researchers with the Florida Fish and Wildlife Conservation Commission, who helped me acquire the INBS data; the NOAA Geophysical Data Center, which answered my questions about the Defense Meteorological Satellite Program imagery; the University of Central Florida’s Marine Turtle Research Group, which took me on several turtle walks; and the Mote Marine Laboratory, for its inspirational display on the effects of artificial light on sea turtles. Most of all I want to thank my parents, who supported me during this eight-month project.

 

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